
- •Contents
- •Preface
- •1 Spread spectrum signals and systems
- •1.1 Basic definition
- •1.2 Historical sketch
- •2 Classical reception problems and signal design
- •2.1 Gaussian channel, general reception problem and optimal decision rules
- •2.2 Binary data transmission (deterministic signals)
- •2.3 M-ary data transmission: deterministic signals
- •2.4 Complex envelope of a bandpass signal
- •2.5 M-ary data transmission: noncoherent signals
- •2.6 Trade-off between orthogonal-coding gain and bandwidth
- •2.7 Examples of orthogonal signal sets
- •2.7.1 Time-shift coding
- •2.7.2 Frequency-shift coding
- •2.7.3 Spread spectrum orthogonal coding
- •2.8 Signal parameter estimation
- •2.8.1 Problem statement and estimation rule
- •2.8.2 Estimation accuracy
- •2.9 Amplitude estimation
- •2.10 Phase estimation
- •2.11 Autocorrelation function and matched filter response
- •2.12 Estimation of the bandpass signal time delay
- •2.12.1 Estimation algorithm
- •2.12.2 Estimation accuracy
- •2.13 Estimation of carrier frequency
- •2.14 Simultaneous estimation of time delay and frequency
- •2.15 Signal resolution
- •2.16 Summary
- •Problems
- •Matlab-based problems
- •3 Merits of spread spectrum
- •3.1 Jamming immunity
- •3.1.1 Narrowband jammer
- •3.1.2 Barrage jammer
- •3.2 Low probability of detection
- •3.3 Signal structure secrecy
- •3.4 Electromagnetic compatibility
- •3.5 Propagation effects in wireless systems
- •3.5.1 Free-space propagation
- •3.5.2 Shadowing
- •3.5.3 Multipath fading
- •3.5.4 Performance analysis
- •3.6 Diversity
- •3.6.1 Combining modes
- •3.6.2 Arranging diversity branches
- •3.7 Multipath diversity and RAKE receiver
- •Problems
- •Matlab-based problems
- •4 Multiuser environment: code division multiple access
- •4.1 Multiuser systems and the multiple access problem
- •4.2 Frequency division multiple access
- •4.3 Time division multiple access
- •4.4 Synchronous code division multiple access
- •4.5 Asynchronous CDMA
- •4.6 Asynchronous CDMA in the cellular networks
- •4.6.1 The resource reuse problem and cellular systems
- •4.6.2 Number of users per cell in asynchronous CDMA
- •Problems
- •Matlab-based problems
- •5 Discrete spread spectrum signals
- •5.1 Spread spectrum modulation
- •5.2 General model and categorization of discrete signals
- •5.3 Correlation functions of APSK signals
- •5.4 Calculating correlation functions of code sequences
- •5.5 Correlation functions of FSK signals
- •5.6 Processing gain of discrete signals
- •Problems
- •Matlab-based problems
- •6 Spread spectrum signals for time measurement, synchronization and time-resolution
- •6.1 Demands on ACF: revisited
- •6.2 Signals with continuous frequency modulation
- •6.3 Criterion of good aperiodic ACF of APSK signals
- •6.4 Optimization of aperiodic PSK signals
- •6.5 Perfect periodic ACF: minimax binary sequences
- •6.6 Initial knowledge on finite fields and linear sequences
- •6.6.1 Definition of a finite field
- •6.6.2 Linear sequences over finite fields
- •6.6.3 m-sequences
- •6.7 Periodic ACF of m-sequences
- •6.8 More about finite fields
- •6.9 Legendre sequences
- •6.10 Binary codes with good aperiodic ACF: revisited
- •6.11 Sequences with perfect periodic ACF
- •6.11.1 Binary non-antipodal sequences
- •6.11.2 Polyphase codes
- •6.11.3 Ternary sequences
- •6.12 Suppression of sidelobes along the delay axis
- •6.12.1 Sidelobe suppression filter
- •6.12.2 SNR loss calculation
- •6.13 FSK signals with optimal aperiodic ACF
- •Problems
- •Matlab-based problems
- •7 Spread spectrum signature ensembles for CDMA applications
- •7.1 Data transmission via spread spectrum
- •7.1.1 Direct sequence spreading: BPSK data modulation and binary signatures
- •7.1.2 DS spreading: general case
- •7.1.3 Frequency hopping spreading
- •7.2 Designing signature ensembles for synchronous DS CDMA
- •7.2.1 Problem formulation
- •7.2.2 Optimizing signature sets in minimum distance
- •7.2.3 Welch-bound sequences
- •7.3 Approaches to designing signature ensembles for asynchronous DS CDMA
- •7.4 Time-offset signatures for asynchronous CDMA
- •7.5 Examples of minimax signature ensembles
- •7.5.1 Frequency-offset binary m-sequences
- •7.5.2 Gold sets
- •7.5.3 Kasami sets and their extensions
- •7.5.4 Kamaletdinov ensembles
- •Problems
- •Matlab-based problems
- •8 DS spread spectrum signal acquisition and tracking
- •8.1 Acquisition and tracking procedures
- •8.2 Serial search
- •8.2.1 Algorithm model
- •8.2.2 Probability of correct acquisition and average number of steps
- •8.2.3 Minimizing average acquisition time
- •8.3 Acquisition acceleration techniques
- •8.3.1 Problem statement
- •8.3.2 Sequential cell examining
- •8.3.3 Serial-parallel search
- •8.3.4 Rapid acquisition sequences
- •8.4 Code tracking
- •8.4.1 Delay estimation by tracking
- •8.4.2 Early–late DLL discriminators
- •8.4.3 DLL noise performance
- •Problems
- •Matlab-based problems
- •9 Channel coding in spread spectrum systems
- •9.1 Preliminary notes and terminology
- •9.2 Error-detecting block codes
- •9.2.1 Binary block codes and detection capability
- •9.2.2 Linear codes and their polynomial representation
- •9.2.3 Syndrome calculation and error detection
- •9.2.4 Choice of generator polynomials for CRC
- •9.3 Convolutional codes
- •9.3.1 Convolutional encoder
- •9.3.2 Trellis diagram, free distance and asymptotic coding gain
- •9.3.3 The Viterbi decoding algorithm
- •9.3.4 Applications
- •9.4 Turbo codes
- •9.4.1 Turbo encoders
- •9.4.2 Iterative decoding
- •9.4.3 Performance
- •9.4.4 Applications
- •9.5 Channel interleaving
- •Problems
- •Matlab-based problems
- •10 Some advancements in spread spectrum systems development
- •10.1 Multiuser reception and suppressing MAI
- •10.1.1 Optimal (ML) multiuser rule for synchronous CDMA
- •10.1.2 Decorrelating algorithm
- •10.1.3 Minimum mean-square error detection
- •10.1.4 Blind MMSE detector
- •10.1.5 Interference cancellation
- •10.1.6 Asynchronous multiuser detectors
- •10.2 Multicarrier modulation and OFDM
- •10.2.1 Multicarrier DS CDMA
- •10.2.2 Conventional MC transmission and OFDM
- •10.2.3 Multicarrier CDMA
- •10.2.4 Applications
- •10.3 Transmit diversity and space–time coding in CDMA systems
- •10.3.1 Transmit diversity and the space–time coding problem
- •10.3.2 Efficiency of transmit diversity
- •10.3.3 Time-switched space–time code
- •10.3.4 Alamouti space–time code
- •10.3.5 Transmit diversity in spread spectrum applications
- •Problems
- •Matlab-based problems
- •11 Examples of operational wireless spread spectrum systems
- •11.1 Preliminary remarks
- •11.2 Global positioning system
- •11.2.1 General system principles and architecture
- •11.2.2 GPS ranging signals
- •11.2.3 Signal processing
- •11.2.4 Accuracy
- •11.2.5 GLONASS and GNSS
- •11.2.6 Applications
- •11.3 Air interfaces cdmaOne (IS-95) and cdma2000
- •11.3.1 Introductory remarks
- •11.3.2 Spreading codes of IS-95
- •11.3.3 Forward link channels of IS-95
- •11.3.3.1 Pilot channel
- •11.3.3.2 Synchronization channel
- •11.3.3.3 Paging channels
- •11.3.3.4 Traffic channels
- •11.3.3.5 Forward link modulation
- •11.3.3.6 MS processing of forward link signal
- •11.3.4 Reverse link of IS-95
- •11.3.4.1 Reverse link traffic channel
- •11.3.4.2 Access channel
- •11.3.4.3 Reverse link modulation
- •11.3.5 Evolution of air interface cdmaOne to cdma2000
- •11.4 Air interface UMTS
- •11.4.1 Preliminaries
- •11.4.2 Types of UMTS channels
- •11.4.3 Dedicated physical uplink channels
- •11.4.4 Common physical uplink channels
- •11.4.5 Uplink channelization codes
- •11.4.6 Uplink scrambling
- •11.4.7 Mapping downlink transport channels to physical channels
- •11.4.8 Downlink physical channels format
- •11.4.9 Downlink channelization codes
- •11.4.10 Downlink scrambling codes
- •11.4.11 Synchronization channel
- •11.4.11.1 General structure
- •11.4.11.2 Primary synchronization code
- •11.4.11.3 Secondary synchronization code
- •References
- •Index

Operational wireless spread spectrum systems |
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increase or reduction of MS power, respectively. To insert the commands into the forward link signal every 20 ms frame after the interleaver is divided into 16 power control groups (PCG), each spanning 1.25 ms or 19:2 103 1:25 10 3 ¼ 24 code symbols of the 19.2 kbps codestream. In every PCG a single power control bit overwrites two code symbols. The MS receiver, knowing the positions of overwritten symbols (i.e. power control bits), excludes them from the decoding procedure as having nothing to do with the message contents. This is entirely equivalent to replacing an original convolutional code by a punctured one (see Section 9.3), and its negative effect on the code correction capability is believed to be partly mitigated by random positioning of the power control bits within PCG. The pseudorandom sequence at the output of the first decimator of Figure 11.3 has the same rate as the codestream, i.e. 19.2 kcps. During one 1.25 ms PCG there are 24 chips of this sequence. The last four of them are read as a binary number with the 24th chip giving the most significant bit. This number, ranging from 0 to 15, is used as a position number of the power control bit in the next but one group after the current one. Thus, the power control bit may take randomly any position out of the first 16 in every PCG. In Figure 11.3 the units implementing positioning and inserting power control bits are denoted as ‘PC bit positioning’ and ‘Multiplexer’.
11.3.3.5 Forward link modulation
Figure 11.4 presents the block-diagram of the forward link modulator. Output voltages of all physical channels of BS are first weighted by appropriate gains to realize forward link power control. Every MS periodically informs the BS about the reliability of data received, and the BS properly adjusts the power level of the signal in the traffic channel assigned to this specific MS to maintain the data reception quality above the predetermined threshold. The weighted channel signals are then summed in the adder and fed in
From pilot, synchronization, paging and traffic channels
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Figure 11.4 IS-95 forward link modulator
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Spread Spectrum and CDMA |
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parallel to the in-phase and quadrature branches of the modulator to be multiplied by the binary PN-I, PN-Q codes (see Section 11.3.2) and shaped in the frequency domain by the baseband filters. The multiplication of the in-phase and quadrature signals by cosine and sine CW components of frequency f0 with their subsequent summation performs up-conversion of the BS signal and finishes the modulation process. As is seen, the input baseband signal in both branches is the same. As such, it is a sum of multiple binary voltages, i.e. is multilevel real. Assume for a while that there is only a single physical baseband channel fed immediately to the modulator branches without summation with other channels. We may postulate that each physical channel is processed this way, i.e. there are as many modulator branch pairs as channels and the outputs of all these parallel modulators are added up coherently. Since the scheme of Figure 11.4 is linear, and hence the superposition principle is valid, its output effect is identical to that of the hypothetical scheme above, i.e. with individually modulated channels. That is why we may say that in the forward link of IS-95 DS spreading is used where the binary datastream (channelized by a Walsh function) modulates the QPSK spreading code (see Section 7.1). Since the rate of the codestream at the modulator input is 19.2 kbps, each symbol has duration covering 64 short code chips. Hence, the forward link spreading factor is 64.
It is worth noting that the long code plays no role in DS spreading of the forward link signal, taking part only in data encryption and power control bit positioning. It is often said that forward link spreading is done by both Walsh codes and short PN-codes. Yet, conceptually classifying Walsh functions as channelizing and PN-codes as spreading may look more convenient.
11.3.3.6 MS processing of forward link signal
Signal processing in the MS receiver rests on the classic procedures discussed in depth in the previous chapters. On successful acquisition of a pilot signal, the receiver DLL pulls in and continuously tracks the short code of the contacted BS. The local replica of the short code produced by DLL serves for despreading the received signal. The outcome of the despread pilot channel is a ‘pure’ CW carrier down-converted to appropriate intermediate frequency. A phase-locked loop tunes the local crystal oscillator to be coherent with this CW signal, providing thereby the reference for coherent data demodulation. After demodulation and deinterleaving the data transmitted over synchronization, paging and traffic channels are separated from each other in correlators using Walsh-sequence references, decoded by the Viterbi algorithm and used according to their destination. For example, a digital-to-analog converter transforms speech data of the traffic channel into voltage, which becomes audible with the aid of an earphone.
Every MS receiver contains several (four or more) parallel channels capable of searching and tracking the pilot signal. One goal of it is arranging the RAKE receiver, which realizes the multipath diversity benefit of spread spectrum (see Section 3.7). Typically at least three such channels are used to implement RAKE fingers. Another procedure requiring autonomous pilot signal channels in the MS receiver is handover. A reserve correlator (or set of them) performs permanent scanning of the time domain, trying to determine if signals of other BSs are present, possibly more intense and